Learning from Instructional Videos.
The interest has dramatically increased in recent years in understanding human behaviors by analyzing instructional videos [1]}, [2]}.
Event discovery tasks such as action recognition and temporal action segmentation [3]}, [4]}, [5]},
state understanding [6]}, and video summarization / captioning [7]}, [1]} study recognition of human actions in video sequences.
The others works [9]} perform egocentric action anticipation model the relationships between past, future events, and incomplete observations.
Action label prediction [10]}, [11]}
addresses the problem of anticipating all activities within a time horizon. However, the correct answer is often not unique due to the large uncertainty in human actions. Unlike the previous works that predict "what is happening" or "what is going to happen", we focus on understanding decision-making processes given the start observation and the visual goal.
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